CN115988245B - Smart television advertisement recommendation method based on secure multiparty calculation privacy information retrieval - Google Patents
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention relates to the field of intelligent television advertisement pushing, in particular to an intelligent television advertisement recommending method based on safe multiparty calculation privacy information retrieval, which greatly improves the protection capability of user information. The scheme comprises the following steps: the advertiser negotiates a unique user identifier with a television manufacturer, the advertiser extracts a first data set only containing the unique user identifier from an original data set, the television manufacturer randomly simulates and generates a second data set according to query data, the first data set and the second data set are intersected to obtain an intersection data set, the advertiser extracts corresponding user tag data from the original data set to obtain a third data set, the advertiser starts libOTe a server, the third data set is taken as a libOTe data set, the television manufacturer starts libOTe a client, user tag data of the third data set for application is obtained according to indexes, and the television manufacturer requests corresponding advertisement content from the advertiser according to the corresponding user tag data. The method and the device are suitable for advertisement pushing of the intelligent television.
Description
Technical Field
The invention relates to the field of intelligent television advertisement pushing, in particular to an intelligent television advertisement recommendation method based on secure multiparty computing privacy information retrieval.
Background
OTT (Over The Top) refers to that an internet company takes an internet smart television and the like as a platform, and provides services such as video, games, shopping and the like for users on the public internet. In the big data age, OTT also becomes the most extensive smart television desktop advertising content delivery form. For many brands of enterprises, in the context of big data marketing, in order to improve advertisement conversion rate, refined operation is the mainstream. Therefore, after purchasing the intelligent television advertisement poster of the television manufacturer, the advertiser needs to put different advertisement contents on the poster according to different user labels. Namely: according to the user picture intelligent recommendation advertisement content or according to the browsing interest change of the user, the advertisement content is replaced in time.
In the refined operation scheme of OTT, in order to realize personalized advertisement recommendation, user tags of users in an advertisement platform in front of television equipment need to be identified, and an advertiser puts advertisements according to different user tags. Thus, advertisers and television vendors need to negotiate a unique identification of users present on the respective platforms to associate users of the advertising platforms with users of the television platforms. At present, common and effective association identifiers are real unique identifiers such as mobile phone numbers, mailboxes and the like. Typically, these user identifications relate to personal privacy information. When the television OTT component uploads the unique user identifier through an API interface provided by an advertiser, there is a problem of leakage of user privacy data. In particular, when the television user is not the user of the advertisement platform, the unique identification information of the television user is directly exposed to the advertiser, so that the information of the user is revealed.
Disclosure of Invention
The invention aims to provide the intelligent television advertisement recommendation method based on secure multiparty calculation privacy information retrieval, which greatly improves the protection capability of user information and ensures the security of the user information.
The invention adopts the following technical scheme to realize the aim, and the intelligent television advertisement recommendation method based on the secure multiparty calculation privacy information retrieval is applied to an advertisement recommendation system, wherein the advertisement recommendation system comprises an advertiser and a television manufacturer, the advertiser is a data provider and holds an original data set, the original data set comprises a user tag data set, the user tag data set corresponds to various user tag data, the television manufacturer provides query data for a data query party, and the query data belongs to the user tag data, and the method comprises the following steps:
step 1, negotiating and determining a unique user identifier by an advertiser and a television manufacturer, wherein the unique user identifier is one of user tag data in a user tag data set;
Step 2, the advertiser extracts a first data set only containing the unique user identifier from the original data set according to the unique user identifier;
step 3, the television manufacturer randomly simulates and generates a second data set according to the query data, wherein the second data set comprises the query data and a plurality of data identical to the data in the first data set, and the query data belongs to a unique identifier;
Step 4, intersection of the first data set and the second data set is obtained, an intersection data set is obtained, and an index of query data in the intersection data set is obtained;
step 5, traversing elements in the intersection data set by the advertiser, extracting corresponding user tag data from the original data set, and obtaining a third data set, wherein the sequence of data in the third data set is consistent with that of data in the intersection data set;
step 6, starting libOTe a server by the advertiser, and taking the third data set as a libOTe data set;
Step 7, starting libOTe the client by the television manufacturer, and acquiring corresponding user tag data in the third data set according to the index;
and 8, the television manufacturer requests corresponding advertisement content from the advertiser according to the corresponding user tag data.
The invention generates the second data set by random simulation of the query data, wherein the second data set comprises the query data and a plurality of data identical to the data in the first data set, so that the intersection data obtained by intersection with the first data set contains a plurality of intersection elements, and information leakage caused by directly passing through single query data is avoided.
LibOTe (Oblivious Transfer, OT) adopts an 'n-select 1' careless transmission technology to realize private information retrieval, complete trace inquiry and avoid leakage of inquiry data.
Further, in step 4, obtaining an intersection set by intersecting the first data set and the second data set, and obtaining an index of the query data in the intersection set specifically includes:
Intersecting the first data set and the second data set based on libPSI to obtain an index set, wherein each element in the index set is an index of each intersection element in the second data set;
Traversing indexes in the index set by a television manufacturer, extracting corresponding elements from the second data set according to the indexes to obtain a first intersection, wherein the first intersection is used as an intersection data set;
an index of query data in the first intersection is obtained.
LibPSI allow the participants to calculate intersections using their respective data sets without revealing any data outside the intersections and returning an index, improving the security of the data.
Further, in step 4, after obtaining the index of the query data in the first intersection, the method further includes: the television vendor sends the first intersection to the advertiser.
Further, in step 5, the advertiser traverses the elements in the intersection dataset, extracts corresponding user tag data from the original dataset, and the obtaining the third dataset specifically includes:
the advertiser traverses the elements in the first intersection, extracts corresponding user tag data from the original dataset, and obtains a third dataset.
Further, the unique user identifier is a user mobile phone number, a user mailbox or a user identity card number.
The beneficial effects of the invention are as follows:
The invention can complete the user label inquiry of the television user in the advertisement platform on the premise of not exposing the unique identification of the television platform user by the safe multiparty computing technologies such as intersection of the privacy set and the privacy information retrieval, thereby completing personalized advertisement recommendation. The protection capability of the user information is greatly improved.
Drawings
Fig. 1 is a flowchart of a smart tv advertisement recommendation method based on secure multiparty computing privacy information retrieval provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention discloses an intelligent television advertisement recommendation method based on secure multiparty calculation privacy information retrieval, which is applied to an advertisement recommendation system, wherein the advertisement recommendation system comprises an advertiser and a television manufacturer, the advertiser is a data provider and holds an original data set, the original data set comprises a user tag data set, the user tag data set corresponds to various user tag data, the television manufacturer provides query data for a data query party, and the query data belongs to the user tag data, and the method comprises the following steps:
step 1, negotiating and determining a unique user identifier by an advertiser and a television manufacturer, wherein the unique user identifier is one of user tag data in a user tag data set;
The user tag data set and the user tag data are in one-to-many relation, and the user tag data comprise a user telephone number, an identity card number, a mailbox, an interest and a like. Specifically, the advertiser and television manufacturer may negotiate a telephone number, an identification card number, or a mailbox for the unique identification of the user.
Step 2, the advertiser extracts a first data set only containing the unique user identifier from the original data set according to the unique user identifier;
specifically, if the advertiser negotiates with the television manufacturer to determine that the telephone number is the unique user identification, the advertiser extracts a first data set containing only the user telephone number from the original data set according to the user telephone number.
Step 3, the television manufacturer randomly simulates and generates a second data set according to the query data, wherein the second data set comprises the query data and a plurality of data identical to the data in the first data set, and the query data belongs to a unique identifier;
in particular, the television manufacturer provides a telephone number as a query condition, so as to avoid leakage of single data, and expands the query data, namely the telephone number, so that the intersection of the second data set and the first data set comprises a plurality of intersection elements.
Step 4, intersection of the first data set and the second data set is obtained, an intersection data set is obtained, and an index of query data in the intersection data set is obtained;
Step 5, traversing elements in the intersection data set by the advertiser, extracting corresponding user tag data from the original data set, and obtaining a third data set, wherein the sequence of data in the third data set is consistent with that of data in the intersection data set; the third data set includes other user tag data, such as user data characteristics of name, mailbox, identification number, hobbies, etc., corresponding to the same phone number and corresponding user tag data.
Step 6, starting libOTe a server by the advertiser, and taking the third data set as a libOTe data set;
Step 7, starting libOTe the client by the television manufacturer, and acquiring corresponding user tag data in the third data set according to the index;
and 8, the television manufacturer requests corresponding advertisement content from the advertiser according to the corresponding user tag data.
Specifically, the television manufacturer obtains other information under the corresponding user tag data in the third data set according to the query data, namely the index of the telephone number, for example, the television manufacturer can obtain the interest and hobbies corresponding to the user, the television manufacturer requests advertisement content corresponding to the interest and hobbies to the advertiser according to the interest and hobbies user tag, if the interest and hobbies are watching a movie, the advertiser provides a trailer advertisement of the movie to the television manufacturer, and the television manufacturer presents the advertisement content at the corresponding position of the corresponding intelligent television to complete personalized advertisement pushing.
As shown in fig. 1, a flowchart of a smart tv advertisement recommendation method based on secure multiparty computing privacy information retrieval provided in an embodiment of the present invention includes four stages: a data preprocessing stage, a PSI calculation stage, a PIR calculation stage and an advertisement pushing stage.
In this embodiment, the advertiser is a data provider, acting as a 0-party participant in secure multiparty computing; television vendors are querying parties and act as 1-party participants in secure multi-party computing. Party 0 has a data set of size n containing various user tag data, such as tel: user mobile phone number, tag: in the advertisement platform, the user tag, namely the user mobile phone number is a tag of the user.
Parties 0 and 1 negotiate to use tel as the user unique identity. Namely: in each inquiry request, the 1 side carries one tel, and the tag corresponding to the corresponding tel in the 0 side data set is searched. In addition, in the query process, the party 0 cannot acquire the query information of the party 1 and the retrieved data item.
If the data set held by party 0 is 500 ten thousand in size, denoted by P. The mobile phone number held by the 1 party is denoted by t;
Then, in the data preprocessing stage, party 0 needs to comb out a dataset containing only tels based on P, denoted by a. The 1-party needs to construct a data set with a size of 1 ten thousand randomly according to t, and only tel is contained, denoted by B.
In the PSI calculation stage, parties 0 and 1 calculate the intersection of A and B based on PSI technology, and the intersection is denoted by I. Namely: i=ajb. PSI technology allows participants to compute intersections using their respective data sets through a series of underlying cryptographic techniques, without revealing any data outside the intersections.
In the PIR calculation phase, party 0 first clusters out a subset P' of P based on intersection I. Party 1 queries the tag of t in P' by "select 1" inadvertently transfer (Oblivious Transfer, OT) technique. The OT is a cryptographic protocol, which makes the data party unable to know the query condition and the detected result of the query party, and also can ensure that the query party can only obtain one result, thereby protecting the privacy information of the query party and the data party. Therefore, through PIR inquiry, the 1 party can be ensured to finish inquiry under the condition that inquiry information is not revealed after the inquiry request is submitted to the 0 party, and the 0 party does not know the inquiry information of the 1 party and the searched data item in the process.
Finally, in the advertisement pushing stage, the 1 side carries the tag searched in the PIR calculation stage, requests the advertisement pulling interface provided by the 0 side, and the 0 side responds to the corresponding advertisement content according to the tag to complete advertisement pushing.
Based on the above principle, the scheme provided by the embodiment of the invention comprises the following detailed steps:
s1, negotiating a user unique identification by the party 0 and the party 1, and assuming that: tel.
And S2, the party 0 organizes a data set A only containing tel according to the negotiated identification tel and the data set P held by the party 0.
And S3, randomly simulating to generate a data set B which is 1 ten thousand in size and only contains tel according to t (namely the inquired telephone number) held by the party 1. Note that t e B needs to be made, while 1 calculates the index of t in B (starting from 0), denoted by i'.
The S4, 0, and 1 sides intersect A, B based on libPSI. libPSI is a privacy intersection source library that implements a number of PSI algorithms. After calculation by libPSI, if an intersection exists between A and B, a set I' containing the index can be obtained on the 1 side. The elements in I 'are the indices of each intersection element in B, and these indices are written to I' out of order.
And S5, judging whether the I 'belongs to the I' or not by the 1 side. If then the process returns to step S3. If I '. Epsilon.I', then the subsequent steps continue to be performed.
S6, traversing the index in the I' by the 1 side, taking out the element corresponding to the index in the B, and sequentially writing the element into an intersection I, namely: i=a n B, t e I, t e a, t e B because .
And S7, calculating an index of t in I by the 1-side, wherein the index is denoted by I. Then, party 1 passes intersection I to party 0 through the http interface. After receiving I, party 0 needs to ensure that the element sequence in I is not changed.
And S8, traversing the elements in the I by the 0-side, and sequentially writing the corresponding data in the P into a set P'. Namely: p 'is a subset of P, and the order of P' on tel columns is consistent with I.
S9, then, based on libOTe, parties 0 and 1 adopt an 'n-selected 1' careless transmission (Oblivious Transfer, OT) technology to realize private information retrieval and complete the trace inquiry. libOTe is an open source library implementing various OT algorithms.
S10, firstly, enabling libOTe a server side to be started by the 0 side, and taking the set P' as a libOTe data set.
S11, then, the 1 side starts libOTe the client program and designates the data index i to be queried. Namely: the 1 st party requests to acquire the ith record in the 0 th party data set P'.
S12, after the ith record in the P' is queried in the 1 st party, other information under the tag corresponding to t can be obtained, and the information is represented by f.
S13, carrying f by the 1 party, requesting an advertisement interface of the 0 party, and completing the operation of pulling the advertisement content according to the user tag f on the premise of not exposing t to the 0 party.
And S14, the 1 party presents advertisement content at the corresponding position of the intelligent television to complete personalized advertisement pushing.
In summary, the invention can complete the user tag inquiry of the television user in the advertisement platform on the premise of not exposing the unique identifier of the television platform user by the security multiparty computing technologies such as intersection of the privacy set and the privacy information retrieval, thereby completing personalized advertisement recommendation, greatly improving the protection capability of the user information and guaranteeing the security of the user information.
Claims (2)
1. The intelligent television advertisement recommendation method based on secure multiparty calculation privacy information retrieval is applied to an advertisement recommendation system, the advertisement recommendation system comprises an advertiser and a television manufacturer, the advertiser is a data provider and holds an original data set, the original data set comprises a user tag data set, the user tag data set comprises various user tag data, the television manufacturer provides query data for a data query party, and the query data belongs to the user tag data, and the intelligent television advertisement recommendation method is characterized by comprising the following steps:
step 1, negotiating and determining a unique user identifier by an advertiser and a television manufacturer, wherein the unique user identifier is one of user tag data in a user tag data set;
Step 2, the advertiser extracts a first data set only containing the unique user identifier from the original data set according to the unique user identifier;
step 3, the television manufacturer randomly simulates and generates a second data set according to the query data, wherein the second data set comprises the query data and a plurality of data identical to the data in the first data set, and the query data belongs to a unique identifier;
step 4, the advertiser and television manufacturer calculate intersections of the first data set and the second data set based on libPSI to obtain an index set, wherein each element in the index set is an index of each intersection element in the second data set;
Traversing indexes in the index set by a television manufacturer, extracting corresponding elements from the second data set according to the indexes to obtain a first intersection, taking the first intersection as an intersection data set, acquiring indexes of query data in the first intersection, and sending the first intersection to an advertiser;
step 5, traversing elements in the intersection data set by the advertiser, extracting corresponding user tag data from the original data set, and obtaining a third data set, wherein the sequence of data in the third data set is consistent with that of data in the intersection data set;
step 6, starting libOTe a server by the advertiser, and taking the third data set as a libOTe data set;
Step 7, starting libOTe the client by the television manufacturer, and acquiring corresponding user tag data in the third data set according to the index;
and 8, the television manufacturer requests corresponding advertisement content from the advertiser according to the corresponding user tag data.
2. The smart tv advertisement recommendation method based on secure multiparty computing privacy information retrieval according to claim 1, wherein the user unique identifier is a user phone number, a user mailbox or a user identification card number.
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